Analyze theoretical and observed masses across single tests. See absolute, relative, and ppm deviations instantly. Make cleaner chemistry decisions using organized numeric error summaries.
| Sample | Theoretical Mass (mg) | Observed Trials (mg) | Mean Observed (mg) | Percent Error (%) |
|---|---|---|---|---|
| NaCl Standard A | 250.000 | 249.92, 250.11, 249.98, 250.03, 249.95 | 249.998 | -0.0008 |
| Copper Sulfate B | 125.000 | 124.86, 124.91, 124.88, 124.94 | 124.8975 | -0.0820 |
| Organic Reference C | 80.500 | 80.62, 80.54, 80.49, 80.51 | 80.5400 | 0.0497 |
Signed Error = Observed Mean − Theoretical Mass
Absolute Error = |Observed Mean − Theoretical Mass|
Relative Error = Absolute Error ÷ Theoretical Mass
Percent Error = ((Observed Mean − Theoretical Mass) ÷ Theoretical Mass) × 100
PPM Error = ((Observed Mean − Theoretical Mass) ÷ Theoretical Mass) × 1,000,000
Sample Standard Deviation = √[Σ(xᵢ − x̄)² ÷ (n − 1)]
Standard Error = Standard Deviation ÷ √n
Relative Standard Deviation = (Standard Deviation ÷ Mean Observed) × 100
These formulas help evaluate accuracy, precision, spread, and practical compliance against an allowed chemistry tolerance.
Mass error measures how far an observed mass differs from the theoretical or accepted value. It helps determine method accuracy and reveals whether results are biased high or low.
Repeated measurements often vary slightly. Using the mean reduces random noise and provides a more stable comparison against the theoretical value, especially during precision studies.
Signed error keeps direction, showing whether the result is above or below target. Absolute error removes the sign and shows the size of the deviation only.
PPM error is useful when working with very small deviations, such as analytical chemistry, calibration work, high-resolution mass measurements, and tightly controlled laboratory standards.
Relative standard deviation measures precision. Lower values indicate that repeated measurements cluster closely together, while higher values suggest more spread and weaker repeatability.
Yes. The calculator works with one value or many. With one value, spread statistics like standard deviation become zero because there are no repeated trials.
Choose a tolerance that matches your laboratory method, instrument limits, or quality target. Regulatory methods, SOPs, and validation protocols usually define the acceptable threshold.
Changing units only rescales the numeric mass values. Percent error, relative error, and pass or fail logic remain consistent because they depend on proportional difference.
Important Note: All the Calculators listed in this site are for educational purpose only and we do not guarentee the accuracy of results. Please do consult with other sources as well.